The DOI matches its Crossref record; 80 of the 80 references it cites were found in a registry or an index.
A hybrid ensemble pruning approach based on consensus clustering and multi-objective evolutionary algorithm for sentiment classification
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Cites
Kennedy, J., & Eberhart, R. (2002) · Proceedings of ICNN'95 - International Conference on Neural Networks · doi:10.1109/icnn.1995.488968 · Cited by 58,192
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
Holland, J. H. (1992) · The MIT Press eBooks · doi:10.7551/mitpress/1090.001.0001 · Cited by 47,002
Storn, R., & Price, K. (1997) · Journal of Global Optimization · doi:10.1023/a:1008202821328 · Cited by 29,569
Data mining: concepts and techniques
(2012) · Choice Reviews Online · doi:10.5860/choice.49-3305 · Cited by 28,531
The WEKA data mining software: an update
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H. (2009) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1656274.1656278 · Cited by 17,750
Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00058655 · Cited by 16,325
Data clustering: 50 years beyond K-means
Jain, A. K. (2010) · Pattern Recognition Letters · doi:10.1016/j.patrec.2009.09.011 · Cited by 9,368
Ensemble methods in machine learning
Dietterich, T. G. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-45014-9_1 · Cited by 8,408
(2008) · Data Mining and Market Intelligence for Optimal Marketing Returns · doi:10.4324/9780080878096-12 · Cited by 6,954
Cited by
Sentiment analysis on product reviews based on weighted word embeddings and deep neural networks
Onan, A. (2021) · Concurrency and Computation: Practice and Experience · doi:10.1002/cpe.5909 · Cited by 396
Self-citationMining opinions from instructor evaluation reviews: a deep learning approach
Onan, A. (2020) · Computer Applications in Engineering Education · doi:10.1002/cae.22179 · Cited by 270
Onan, A. (2019) · IEEE Access · doi:10.1109/access.2019.2945911 · Cited by 257
Self-citation
Metadata
- Authors
- Onan, A., Korukoğlu, S., & Bulut, H.
- Venue
- Information Processing & Management
- Publisher
- Elsevier BV
- Published
- 2017-07
- Volume
- 53
- Issue
- 4
- Pages
- 814-833
- ISSN
- 0020-0271 (ISSN-L)
- 0306-4573
- OpenAlex
- W2593914038
- Cited by
- 305
- References
- 80
- FWCI
- 6.56
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Onan, A., Korukoğlu, S., & Bulut, H. (2017). A hybrid ensemble pruning approach based on consensus clustering and multi-objective evolutionary algorithm for sentiment classification. Information Processing & Management. https://doi.org/10.1016/j.ipm.2017.02.008
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
